A data repository may include records storing data of similar types, but in different data formats. The different data formats may not be directly compatible or interchangeable with each other. In an example, a data repository includes fitness data. The records include individuals' weights in different units, such as pounds, kilograms, stones, etc. In another example, a data repository includes financial data. The records include transaction amounts in different currencies, such as U.S. dollar, Euro, Japanese yen, Swiss franc, etc. In another example, a data repository includes vehicle data. The records include vehicles' top speeds in different units, such as miles per hour, kilometers per hour, knots, etc. In another example, a data repository includes inventory data. The records include amounts of inventory in different units, such as ounces, pounds, kilograms, etc. Data of many different similar types may be stored in many different data formats.
When a data repository includes records storing data in different formats, obtaining data in a particular format typically involves retrieving all of the corresponding records from the data repository. For each record where the data is not in the desired format, obtaining the data further involves converting the data from the format in which it was stored to the desired format. As the number of records increases, the computing resources needed to retrieve each record and convert data to the required format increases. Depending on the number of records, retrieving all the records and converting data to the required format may be unacceptably inefficient or even impracticable.
The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.